It is always desired to know the performance of an application running in a networked environment. The application can be a sequence of web pages, each of which needs to be traversed to complete a particular transaction. A typical example of such an application is online shopping cart. It is important to know the critical performance of such an application because it directly impacts the world of customers and consequently, the market. The performance of an application can be gauged in terms of various metrics like response time of the server, transaction throughput and so on and so forth. A log is maintained at the server end to keep a track of a few elements such as time of request, time of response etc. The numerous performance metrics are calculated on the basis of the aforementioned elements.
The web-server log analysis, that exists now, focuses on fetching the raw data from the logs and on analyzing the web logs at a page level, request level or the entire application level. The current technology refers throughput in terms of bytes per second. The responsiveness of the application is viewed at a page level that represents the server processing time for the requests. This raw data is further used as-is to estimate the basic transaction level performance test strategy metrics, more a guesstimate than an accurate figure.
As existing log analysis focuses on extracting the raw data as-is from the production logs and use it to base performance test strategies. This requires lot of manual interpretation and effort in calculating the critical performance metrics. Each entry is seen as isolated and the techniques do not have intelligence built in to view the bunch of entries termed as business transactions together for a particular user. The analysis hence cannot refer throughput in terms of transactions per second and the responsiveness at the transactions level is difficult to compute. This ends up in a few critical bits of information being lost during such raw data interpretation, adding inaccuracies in the performance test strategies and thus, in performance test results.